Vignayanandam Ravindernath Muddapu

The paper develops a computational model of mouse thalamoreticular microcircuitry to study sensory enhancement and sleep spindle properties, revealing mechanisms of network-level activity across brain states.

This paper introduces a reinforcement learning-based deep neural network model to simulate multiple cognitive functions and demonstrates its potential as a testbench for cognitive impairment research.

This paper presents a multiscale computational model of the cortico-basal ganglia system to simulate arm reaching behavior under normal, Parkinsonian, and levodopa conditions, showing how SNc cell loss and medication affect motor performance.

The paper develops a computational model of SNc cells to investigate how energy deficiency contributes to Parkinson's disease neurodegeneration by simulating molecular processes like ATP variation and alpha-synuclein aggregation.

This study uses a multi-scale computational model to show that energy deficiencies and calcium elevation contribute to excitotoxic loss of dopaminergic neurons in Parkinson's disease, with specific therapies halting cell loss.

The paper develops a multiscale computational model of the SNc-striatum system to study LDOPA-induced toxicity in Parkinson's disease and shows that energy deficiency contributes to neurodegeneration.

The paper develops a computational model of dopaminergic cell loss in Parkinson’s disease due to glutamate-induced excitotoxicity and evaluates therapeutic interventions.